The Effects of Performance-Contingent Financial Incentives in Online Labor Markets

Online labor markets such as Amazon Mechanical Turk (MTurk) have emerged as platforms that facilitate the allocation of productive effort across global economies. Many of these markets compensate workers with monetary payments. We study the effects of performance-contingent financial rewards on work quality and worker effort in MTurk via two experiments. We find that the magnitude of performance contingent financial rewards alone affects neither quality nor effort. However, when workers working on two tasks of the same type in a sequence, the change in the magnitude of the reward over the two tasks affects both. In particular, both work quality and worker effort increase (alternatively decrease) as the reward increases (alternatively decreases) for the second task. This suggests the existence of the anchoring effect on workers’ perception of incentives in MTurk and that this effect can be leveraged in workflow design to increasethe effectiveness of financial incentives.Engineering and Applied Science

Foreign Institutional Ownership and the Speed of Leverage Adjustment: International Evidence

Employing a large sample of 7246 firms across 38 economies from 2000 to 2013, we show a positive relation between foreign institutional ownership (FIO) and firms’ speed of leverage adjustment. This positive relation is concentrated for over-leveraged firms that need to decrease financial leverage to rebalance their capital structures. We validate our findings using a 2SLS regression and a DiD estimation to exploit the exogenous variations in FIO generated by the inclusion of MSCI membership and the passage of the JGTRRA. These results suggest that foreign institutional investors play an important monitoring role in mitigating agency conflicts between shareholders and managers. Overall, this paper lends support to the dynamic trade-off theory

Unsupervised Extractive Summarization with Heterogeneous Graph Embeddings for Chinese Document

In the scenario of unsupervised extractive summarization, learning high-quality sentence representations is essential to select salient sentences from the input document. Previous studies focus more on employing statistical approaches or pre-trained language models (PLMs) to extract sentence embeddings, while ignoring the rich information inherent in the heterogeneous types of interaction between words and sentences. In this paper, we are the first to propose an unsupervised extractive summarizaiton method with heterogeneous graph embeddings (HGEs) for Chinese document. A heterogeneous text graph is constructed to capture different granularities of interactions by incorporating graph structural information. Moreover, our proposed graph is general and flexible where additional nodes such as keywords can be easily integrated. Experimental results demonstrate that our method consistently outperforms the strong baseline in three summarization datasets

To What Extent Do Macroeconomic Factors Affect Companies’ Performance?

The main purpose of this study is trying to explore whether the macroeconomic factors will affect corporate performance or not in the UK. Therefore, my study randomly chooses 50 companies from FTSE 350 as the sample dataset for examining the relationship between 10 macroeconomic variables and firm’s performance. Also, there are two models used in my study as the measurements of corporate performance which is based on firm’s market returns (Tobin’s q) and accounting returns (ROA). On the base of using SPSS, the results present that change of 20 years bond yield, change of industrial productivity index (IPI), and change of gross domestic product (GDP) have positively significant effect on firms’ market and accounting returns. On the other hand, the change of oil price reports a negative relation with companies’ market and financial performance. Moreover, change of M0 and M4 present a positive relationship with companies’ market returns and change of unemployment rate has a positive impact on firms’ accounting returns. However, there are three macroeconomic variables, change of exchange rate, change of consumer price index (CPI), and yearly rediscount rate, have no significant effect on firms’ market and accounting performance. The contribution of this study is that it helps managers to pierce the fluctuation of several macroeconomic variables precisely; therefore, mangers can conduct firm’s policy and strategies more accurate and effective. The other contribution of this study is that it offers a clear and general perspective with regard to the decisive factors on corporate performance for the public; therefore, the public can have a better understanding of the companies they want to invest

Using Pattern Recognition for Investment Decision Support in Taiwan Stock Market

In Taiwan stock market, it has been accumulated large amounts of time series stock data and successful investment strategies. The stock price, which is impacted by various factors, is the result of buyer-seller investment strategies. Since the stock price reflects numerous factors, its pattern can be described as the strategies of investors. In this paper, pattern recognition concept is adapted to match the current stock price trend with the repeatedly appearing past price data. Accordingly, a new method is introduced in this research that extracting features quickly from stock time series chart to find out the most critical feature points. The matching can be processed via the corresponding information of the feature points. In other words, the goal is to seek for the historical repeatedly appearing patterns, namely the similar trend, offering the investors to make investment strategies

Expression and prognostic significance of cancer-testis antigens (CTA) in intrahepatic cholagiocarcinoma

<p>Abstract</p> <p>Background</p> <p>Cancer-testis antigens (CTAs) are suitable targets for cancer-specific immunotherapy. The aim of the study is to investigate the expression of CTAs in intrahepatic cholagiocarcinoma (IHCC) and evaluate their potential therapeutic values.</p> <p>Methods</p> <p>Eighty-nine IHCC patients were retrospectively assessed for their expression of CTAs and HLA Class I by immunohistochemistry using the following antibodies: MA454 recognizing MAGE-A1, 57B recognizing multiple MAGE-A (MAGE-A3/A4), E978 recognizing NY-ESO-1, and EMR8-5 recognizing HLA class I. The clinicopathological and prognostic significance of individual CTA markers and their combination were further evaluated.</p> <p>Results</p> <p>The expression rates of MAGE-A1, MAGE-A3/4 and NY-ESO-1 were 29.2%, 27.0% and 22.5%, respectively. The concomitant expression of CTAs and HLA class I antigen was observed in 33.7% of the IHCC tumors. We found that positive MAGE-3/4 expression correlated with larger tumor size (≥ 5 cm), tumor recurrence and poor prognosis. Moreover, we identified 52 cases (58.4%) of IHCC patients with at least one CTA marker expression, and this subgroup displayed a higher frequency of larger tumor size and a shorter survival than the other cases. Furthermore, expression of at least one CTA marker was also an independent prognostic factor in patients with IHCC.</p> <p>Conclusion</p> <p>Our data suggest that specific immunotherapy targeted CTAs might be a novel treatment option for IHCC patients.</p